Coding · Mistral AI

Codestral Base on LiveCodeBench: score, rank and what it means

Codestral Base scores 65.7 on LiveCodeBench, placing it #279 of 600 models in the index. The benchmark average is 61.0 and the leader is Claude Sonnet 4.5 Reasoning at 85.1.

Score
65.7
0–100 scale
Rank
#279
of 600
Percentile
54th
within the index
Benchmark avg
61.0
all models
Leader
85.1
Claude Sonnet 4.5 Reasoning
Gap to leader
19.4
points

Score distribution

The chart shows the top 10 models on LiveCodeBench, with Codestral Base highlighted. Longer bars mean higher scores.

Claude Sonnet 4.5 Reasoning 85.1
Grok 4 Reasoning 85.1
Claude Opus 4.5 85.0
GPT-5.2 Max 84.8
Grok 4 Turbo 84.7
GPT-5.1 Turbo 84.6
GPT-5.2 Pro 84.6
GPT-5.2 Reasoning 84.6
Claude Opus 4.5 Pro 84.1
Gemini 3 Pro Max 83.6

Top 10 leaderboard

#ModelProviderContextInput / 1MAvg score
1 Claude Sonnet 4.5 Reasoning Anthropic 400000 $19.48 87.7
2 Grok 4 Reasoning xAI 2000000 $19.67 87.8
3 Claude Opus 4.5 Anthropic 400000 $19.42 87.7
4 GPT-5.2 Max OpenAI 1000000 $21.39 89.2
5 Grok 4 Turbo xAI 1000000 $19.21 86.7
6 GPT-5.1 Turbo OpenAI 2000000 $19.19 86.1
7 GPT-5.2 Pro OpenAI 2000000 $21.32 89.6
8 GPT-5.2 Reasoning OpenAI 1000000 $20.98 87.5
9 Claude Opus 4.5 Pro Anthropic 200000 $20.98 89.1
10 Gemini 3 Pro Max Google DeepMind 2000000 $20.57 87.9

What this score means

On LiveCodeBench, Codestral Base sits at #279 of 600. The leader, Claude Sonnet 4.5 Reasoning, scores 85.1, so the gap to the top is 19.4 points. The median model in this index scores 64.7, which puts Codestral Base above the midpoint.

Mistral AI models average 58.1 on this benchmark. Codestral Base is 7.6 points above that provider line, so it is a stronger result than the average Mistral AI model.

Among open-weight models, the average is 59.1. Codestral Base is 6.6 points above that group. This is the more useful comparison if you are shortlisting within the same tier rather than across the whole index.

Read a 65.7 as a relative signal, not an absolute guarantee. Benchmark scores depend on prompt format, evaluation harness and contamination controls. Use this page to narrow the shortlist, then test the model on your own data.

Price context

At $3.31 per million input tokens, Codestral Base is below the median input price of $4.00 across the 600 models scored on LiveCodeBench. The models immediately around it in the ranking are shown below so you can compare score and price together.

ModelProviderContextInput / 1MAvg score
Llama 3 Replicate Instruct Replicate 128000 $3.71 75.1
Nemotron 4 Chat NVIDIA 65536 $3.99 75.0
Yi-Large Instruct 01.AI 32768 $3.48 73.4
o4 Nano OpenAI 65536 $8.61 72.0
Codestral Base Mistral AI 8192 $3.31 73.1
Llama 3 Lambda Base Lambda 8192 $3.19 72.9
Nova Lite Reasoning Amazon 32768 $9.92 74.3

Other benchmarks for Codestral Base

BenchmarkScoreRankPercentileRelative
MMLU-Pro 74.1 348 42th
GPQA Diamond 70.4 252 58th
SWE-bench Verified 62.6 264 56th
HumanEval 79.7 240 60th
MATH-500 77.4 267 56th
AIME 2025 68.7 283 53th
IFEval 79.2 347 42th
TruthfulQA 74.3 347 42th
HellaSwag 83.3 311 48th
MMMU 68.3 339 44th
Arena Elo 1371.7 310 48th

FAQ

What score does Codestral Base get on LiveCodeBench?

Codestral Base scores 65.7 on LiveCodeBench in this index. The benchmark average is 61.0 and the top score is 85.1.

How does Codestral Base rank on LiveCodeBench?

It ranks #279 of 600 models, in the 54th percentile. The leader is Claude Sonnet 4.5 Reasoning at 85.1.

Is Codestral Base good at LiveCodeBench?

Yes, relative to the index: it is above the median and inside the top half of scores. The result should be read alongside its price and context window.

How is the LiveCodeBench score calculated?

LiveCodeBench is a coding benchmark. Scores in this index are modelled estimates on a 0–100 scale (or Elo for Arena), derived from capability tier and benchmark difficulty. They are not official leaderboard results.

What does Codestral Base cost?

Codestral Base costs $3.31 per million input tokens and $16.95 per million output tokens.

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